We D03 Limitations of 2D Deghosting and Redatuming in Time-lapse Processing of Towed-streamer Data

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1 We D03 Limitations of 2D Deghosting and Redatuming in Time-lapse Processing of Towed-streamer Data K. Eggenberger* (Schlumberger), P. Caprioli (Schlumberger) & R. Bloor (Schlumberger) SUMMARY Implications to time-lapse seismic are discussed when relying on 2D deghosting and redatuming techniques rather than on 3D algorithms to match deep-tow data with a shallow legacy seismic tow. The analysis at hand, being performed for the first time, not only uses quantitative metrics to allow for a thorough and detailed evaluation of the 4D noise observed, but also capitalizes on new qualitative measures like the stack of the horizontal acceleration component Y for its characterization. The analysis on 2D deghosted and redatumed deep-tow data is performed against a measured shallow-tow witness data set where care was taken not to compromise the 3D propagating wavefield in the pre-processing. Whereas the 2D approach produces good repeatability over laterally non-varying geology, it fails over more complex geology, introducing a coherent error when dealing with out-of-plane energy. Mitigation is available through the use of 3D deghosting and redatuming algorithms, relying on non-aliased spatial bandwidth to further enhance time-lapse repeatability.

2 Introduction Multimeasurement, or multisensor streamers, conceptually introduced by Robertsson et al. (2008), record not only scalar pressure wavefields P, but also vector wavefields of particle motion such as the combination of crossline and vertical acceleration measurements, Y and Z. Based on these additional measurements, Özbek et al. (2010) outlined the theory for a signal processing technique called generalized matching pursuit (GMP) that can realize joint wavefield reconstruction and deghosting in a 3D sense by finding basis functions that model simultaneously the recorded pressure wavefield and as many spatial pressure gradients as may be available, typically P, Y, and Z. This offers to overcome not only the temporal bandwidth limitations targeted by a family of broadband systems, but also the spatial bandwidth limitations inherent to towed marine seismic acquisition. However, it is also possible to use these measurements simply to deghost acquired data along the streamer positions using the pressure P and the vertical acceleration measurement Z, while omitting the crossline acceleration Y, and thereby, reverting to a 2D solution. Caprioli et al. (2012) presented and discussed several strategies on how to deghost the data based on collocating pressure and vertical acceleration measurements. It was shown that the optimal deghosting (ODG) algorithm, introduced by Ӧzdemir et al. (2009), provides up/down separation of the wavefield on the receiver side with an enhanced signalto-noise ratio across the full frequency spectrum compared to other methods. Successful deghosting allows a deep-tow streamer configuration to be chosen, as opposed to the traditional shallow tow of hydrophone-only systems. This benefits from a quieter acquisition environment and from an enhanced spectral response, mostly due to the low-frequency contribution from the receiver ghost. In a timelapse (4D) seismic context, however, where conventional, shallow-towed baselines exist, redatuming of the deep-tow data is required to allow for a meaningful time-lapse comparison. A core element of this process is the capability to deghost and redatum the data with high fidelity. Data acquisition and processing To quantify ODG-based deghosting and redatuming fidelity to match with a shallow-tow legacy seismic data, a 2D over/under field data set recorded in the North Sea was used. The over cable, towed at 8 m of depth, consists of a 2-km streamer comprising only hydrophones. In contrast, the under cable was a 2.4-km multisensor streamer, towed at 30 m of depth, which recorded P and Z, together with the crossline acceleration Y. For the analysis at hand, the latter recording was employed only as a QC measure to identify crossline traveling energy. A single sail line, acquired over a water depth of around 90 m, was used for the analysis, consisting of 601 shots positioned at a depth of 6 m with a single-source shot-point interval of 25 m (Figure 1a). The upper cable then becomes a witness (or benchmark) streamer recording the total pressure wavefield, mimicking at the same time, a possible time-lapse repeat scenario where a deep tow must be redatumed to match a legacy shallowtow data set. This experimental setup also benefits from the minimization of environmental differences like tidal statics, water salinity, and water temperature that are common to production time-lapse seismic measurements. Furthermore, source mispositioning, as a potential source of 4D noise, together with source-strength variability, is avoided; however, receiver mispositioning between the over and under cables can still be a source of non-repeatability, but to a lesser extent than it would be with a repeat tow because of better mechanical control and water currents likely to impact both cables in a similar manner. Finally, the need for demultiple, with multiples generally being a source of non-repeatability, becomes obsolete due to the nature of the experiment. Here, multiples are as repeatable as primary energy, owing to the invariance of the environmental factors mentioned above. One source of inconsistency can be introduced by the use of two different acquisition platforms; whereas, the upper cable is a hydrophone-only cable, the lower cable is a multimeasurement streamer. Small differences in the hydrophone response between these two platforms must, potentially, be alleviated. With these considerations in mind, the processing flow applied is described and illustrated in Figure 1b. The shallow-tow, hydrophone-only data undergo preconditioning as part of the online acquisition system and are then processed offline through common-midpoint (CMP) sorting and stacking using a 1D velocity function that is representative of the survey area. The processing applied to the deep-tow

3 a) b) Figure 1 a) An over/under configuration with mixed acquisition platforms was chosen to obtain the trial data set. The seabed is relatively flat with an average depth of ca. 90 m. b) Schematic processing flow applied. multimeasurement data is more elaborate: it starts with a preconditioning flow similar to the one applied to the shallow tow. The wavefield is decomposed into its up- and downgoing constituents using ODG. The decomposed wavefields are then individually redatumed by wavefield extrapolation from a tow depth of 30 m to the much shallower 8-m datum, and recombined through summation to replicate the hydrophoneonly full-wavefield data. Nominal cable depth values were used in processing. The inline offsets were truncated to match those of the shallow-tow cable and then stacked across the full sail line using the same 1D velocity function as before. To account for subtle differences between the two acquisition platforms and associated online preconditioning flows, a global matching filter was derived poststack in a window around the first breaks and applied to the entire trace length. By time-lapse standards, the workflow applied corresponds to a fast-track processing route, with elements such as time-lapse binning, random noise attenuation, and migration missing. However, the analysis also benefits from the pseudo-4d acquisition design as discussed earlier. Finally, 4D metrics were computed using normalized root mean square (NRMS) and predictability (PRED) as defined by Kragh and Christie (2002). Results and discussion of redatuming and deghosting Given the acquisition and processing details, together with the geological setting, the acquired deeptow data were 2D deghosted and redatumed using the optimal deghosting algorithm and compared with the benchmark data acquired simultaneously in a shallow tow. The final 2D brute stacks, displayed in Figures 2a and 2b, show good similarity, considering that the full data set in Figure 2b was redatumed over 22 m from 30 m to a shallower depth of 8 m. Small, coherent, differences are revealed only when differencing the stacks shown in Figures 2a and 2b. The amplitude spectra in Figure 2c further support the validity of the process and, within the signal frequency range of 3 80 Hz, the two spectra are almost identical, with differences of much less than 0.5 db. Figure 2g shows NRMS and PRED as a function of inline CMP position, exhibiting good repeatability, considering the data and preprocessing constraints. Sources for the non-repeatable 4D noise floor can be found in the different noise characteristics between shallow and deep tow: the latter is much quieter, also benefiting from the optimal combination of P and Z as part of ODG, which is reflected in the redatumed full wavefield of Figure 2b. However, in the context of matching a deep tow with a shallow tow, this benefit is compromised. Given the single-pass experiment, the two main contributors for the coherent residual 4D error are found in the mispositioning between the over and under cable and the 2D deghosting and redatuming technique; the latter is expected to suffer in areas generating considerable out-of-plane energy. Whereas the relation between acquisition mispositioning and 4D noise is well documented in literature (Landrø, 1999), this is not the case for the 2D algorithmic limitations when looking into time-lapse seismic deghosting and redatuming. To decouple and isolate the error introduced by the 2D assumption taken, the analysis is limited in the following to a time window in the middle of the sail line, captured in Figure 2d, which shows the full pressure wavefield, where the repositioning error is very small, barely exceeding 2 m and, hence, minimally contributing to the noise floor. The orangecolored lines at the top of Figure 2 represent the repositioning error between the upper and the lower cable. The source repositioning error is zero as a result of the experiment. Figure 2e shows the stacked section of the Y acceleration for the same subsurface line and the same window with the aim of identifying out-of-plane energy.

4 7 m Over/under cable repositioning error 7 m Over/under cable repositioning error 0 m P stack (8 m) 0 m P stack (8 m) 1.5 s d) 2.0 s Y stack 2.5 s 3.0 s a) P stack (30 m 8 m) e) 4D 8 m 1.5 s 2.0 s 2.5 s 3.0 s b) f) 8m 30m 8m c) 80 db 70 db 60 db NRMS PRED g) 50 db Hz Figure 2 a) 2D brute stack of the full-fold sail line for the hydrophone-only 8-m cable, b) 2D brute stack ODG redatumed from 30 m to 8 m. c) Representative amplitude spectra of these solutions. d) Zoom into the red dotted box shown in a). Subplot e) shows the corresponding stacked Y measurement. f) 4D difference plot of a) and b) within the red dotted box shown in a). The 4D difference has the same amplitude scaling applied as the P stacks. g) NRMS and predictability derived within an analysis window of s. The orange-coloured curves on top of the figure show averaged crossline receiver mispositioning between over and under cables.

5 Because the Y stack captures energy propagating in the crossline direction, it can be used as a proxy to show where the standard 2D inline traveling energy assumption of the deghosting and redatuming applied is violated. The near surface produces crossline traveling energy, most prominently represented through diffractions. Such a dominant event is highlighted by the green full arrow. At around 1 s two-way traveltime, the interval of dipping rotated fault blocks is also visible on the Y stack (green dashed arrows). This confirms the analysis on the legacy pressure-only data that elements of the local geology produce out-of-plane energy. As expected, strong flat events, as seen at 0.75 s and indicated by a black arrow, did not produce crossline traveling energy, supporting the validity of the proxy assertion. When taking the 4D difference between the measured and redatumed pressure wavefield (Figure 2f), there is a strong visual correlation between the energy on the Y component stack (Figure 2e) and the mismatch observed in Figure 2f. The way the wavefield is captured on the two components is, of course, different because they represent different measurements a difference in scalar pressure versus a crossline component of acceleration. Furthermore, the residual energy on the difference stack closely follows the geology trend observed on vintage data, and which is expected to produce 3D wavefield propagation characteristics. Hence, 3D rather than 2D operators, involving the Y component information, ought to be helpful to further lower the redatumed wavefield mismatch. Conclusions In a single-pass experiment with conventional and multimeasurement streamers using a 2D over/under configuration, it is shown both qualitatively and quantitatively that 2D deghosting and redatuming can provide reasonably good repeatability over laterally non-varying geology compared to a measured shallow-tow benchmark. However, it was also shown that, in the presence of crossline propagating energy, the 2D deghosting and redatuming approach has algorithmic limitations and produces 4D noise. This coherent 4D noise correlates well with the energy recorded on the crossline acceleration measurement, capturing out-of-plane traveling energy, but also with the subsurface geology itself, analyzed on vintage seismic data. To further enhance time-lapse repeatability and preserving wavefield fidelity at the same time, 3D operators offer the potential to enhance repeatability even further. Such a 3D methodology requires knowledge of the crossline wavenumber that can be achieved either with very tight streamer spacing that is operationally challenging or by using a multimeasurement streamer. References Caprioli, P. B. A., K.A. Ӧzdemir, A. Ӧzbek, J.E. Kragh, D.-J. van Manen, P.A.F. Christie, and J. Robertsson, 2012, Combination of multi-component streamer pressure and vertical particle velocity theory and application to data: 74th Meeting European Association of Geoscientists & Engineers, Expanded Abstracts, A033. Kragh, E., and P. Christie, 2002, Seismic repeatability, normalized RMS, and predictability: The Leading Edge, 21(7), Landrø, M., 1999, Repeatability issues of 3-D VSP data: Geophysics, 64, Özbek, A., M. Vassallo, K. Özdemir, D.-J. van Manen, and K. Eggenberger, 2010, Crossline wavefield reconstruction from multicomponent streamer data: Part 2 Joint interpolation and 3D up/down separation by generalized matching pursuit: Geophysics, 75, WB69-WB85. Ӧzdemir, K., A. Ӧzbek, P. Caprioli, J. Robertsson, and E. Kragh, 2009, The optimal deghosting algorithm for broadband data combination:, 79th Annual International Meeting, SEG, Expanded Abstracts, Robertsson, J. O. A., I. Moore, M. Vassallo, K. Özdemir, D.-J. van Manen, and A. Özbek, 2008, On the use of multicomponent streamer recordings for reconstruction of pressure wavefields in the crossline direction: Geophysics, 73(5), A45-A49.